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Nonparametric identification in panels using quantiles

Author

Listed:
  • Victor Chernozhukov

    (Institute for Fiscal Studies and MIT)

  • Ivan Fernandez-Val

    (Institute for Fiscal Studies and Boston University)

  • Stefan Hoderlein

    (Institute for Fiscal Studies and Boston College)

  • Whitney K. Newey

    (Institute for Fiscal Studies and MIT)

Abstract

This paper considers identi?cation and estimation of ceteris paribus effects of continuous regressors in nonseparable panel models with time homogeneity. The effects of interest are derivatives of the average and quantile structural functions of the model. We ?nd that these derivatives are identi?ed with two time periods for “stayers”, i.e. for individuals with the same regressor values in two time periods. We show that the identi?cation results carry over to models that allow location and scale time e?ects. We propose nonparametric series methods and a weighted bootstrap scheme to estimate and make inference on the identi?ed e?ects. The bootstrap proposed allows inference for function-valued parameters such as quantile e?ects uniformly over a region of quantile indices and/or regressor values. An empirical application to Engel curve estimation with panel data illustrates the results.

Suggested Citation

  • Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Whitney K. Newey, 2014. "Nonparametric identification in panels using quantiles," CeMMAP working papers CWP54/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:54/14
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    More about this item

    Keywords

    Panel data; nonseparable model; average e?ect; quantile e?ect; Engel curve;
    All these keywords.

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